How do independent lineages respond to similar selective pressures at the genetic level? Does selection affect the same genes, or different genes for the same result? I will address these questions using selection for increased starch content across independent origins of domesticated rice (genus Oryza) as a model system. Rice is uniquely appropriate for this study for three reasons. First, there have been three origins of domesticated rice;two of these origins resulted in the formation of the widely cultivated Asian rice (O. sativa), and the third resulted in the formation of African rice (O. glaberrima). Second, the genes controlling starch biosynthesis have been identified and well characterized. Third, there are two fully sequenced genomes available for rice, making genetic studies extremely tractable. Thus, the system presents a combination of evolutionary history and genetic resources that will make addressing the question of evolution under parallel selection a viable objective. This research proposal has three specific aims: 1) to determine and compare the genomic consequences of domestication in African vs. Asian rice, and to determine the population structure and geographic origin of domesticated rice in Africa, 2) to determine the origin of alleles at starch biosynthesis loci in each domesticated lineage relative to the wild progenitors and to compare these candidate genes to a genome-wide panel of neutral loci, and 3) to determine and compare the signature of selection in genes controlling starch biosynthesis across the three origins of cultivated rice. I will address these questions using thorough sampling of the cultivated species and their wild progenitors combined with sequencing of neutral loci, loci controlling starch biosynthesis, and gene fragments from the regions surrounding starch synthesis loci. Sequence data will be analyzed based on similarity and patterns of nucleotide variation using current population genetic and phylogenetic techniques. This analysis, in combination with an extensive sequence data set, will differentiate the effects of demographic factors from those of selection on genes of interest, something that is difficult to accomplish in most other systems. In combination, the three components of the project will provide valuable insight into the genetic response of independent lineages to parallel selection. The project has important implications for public health, as human pathogens experience similar selective pressures in the form of homogeneous drug treatments across broad geographical areas. Understanding the genetic results of similar selective pressures can allow us to predict the response of pathogens to parallel selection and also to anticipate potentially dangerous scenarios involving recombination among independent lineages subject to the same selective regimes.